Traditional performance analysis of approximation algorithms considers overall performance, while economic fairness analysis focuses on the individual performance each user receiv...
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
In this paper, we deal with the large-scale divisible load problem studied in [12]. We show how to reduce this problem to a classical preemptive scheduling problem on a single mac...
Anne Benoit, Loris Marchal, Jean-Francois Pineau, ...
Heterogeneous computing (HC) environments composed of interconnected machines with varied computational capabilities are well suited to meet the computational demands of large, di...
Tracy D. Braun, Howard Jay Siegel, Anthony A. Maci...
—This paper addresses the problem of frequency domain packet scheduling (FDPS) incorporating spatial division multiplexing (SDM) multiple input multiple output (MIMO) techniques ...
Suk-Bok Lee, Sayantan Choudhury, Ahmad Khoshnevis,...